@inproceedings{afde1f5b65984d6080533cababe598e3,
title = "Beamforming and power allocation for energy-efficient massive MIMO",
abstract = "Massive multiple input multiple output (MIMO) has emerged as a promising technology, which utilizes a large number of antennas at base stations (BSs) to significantly improve the spectral efficiency in terms of bits/s/Hz while reducing the radiated signal power. A critical issue with massive MIMO is the costly circuit power consumption, which is proportional to the number of antennas. This paper develops low-complexity power allocation techniques to apply beamforming and to maximize the energy efficiency of massive MIMO while meeting users' quality-of-service requirements. Algorithms of low computational complexity with rapid convergence are proposed to solve for the optimal beamformer in this sense. Numerical examples are provided to show the merit of the proposed computational approach.",
author = "Nguyen, {Long D.} and Tuan, {Hoang D.} and Duong, {Trung Q.} and Poor, {H. Vincent}",
note = "Publisher Copyright: {\textcopyright} 2017 IEEE.; 2017 22nd International Conference on Digital Signal Processing, DSP 2017 ; Conference date: 23-08-2017 Through 25-08-2017",
year = "2017",
month = nov,
day = "3",
doi = "10.1109/ICDSP.2017.8096127",
language = "English (US)",
series = "International Conference on Digital Signal Processing, DSP",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "2017 22nd International Conference on Digital Signal Processing, DSP 2017",
address = "United States",
}